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NTIS 바로가기정보처리학회논문지. KIPS transactions on software and data engineering. 소프트웨어 및 데이터 공학, v.7 no.6, 2018년, pp.205 - 220
류덕산 (KAIST, School of Computing) , 백종문 (KAIST, School of Computing)
Software defect prediction is helpful for allocating valuable project resources effectively for software quality assurance activities thanks to focusing on the identified fault-prone modules. If historical data collected within a company is sufficient, a Within-Project Defect Prediction (WPDP) can b...
S. Kim, E. Whitehead, and Y. Zhang, "Classifying software changes: Clean or buggy?," Softw. Eng. IEEE Trans., Vol. 34, No.2, pp.181-196, 2008.
K. O. Elish and M. O. Elish, "Predicting defect-prone software modules using support vector machines," J. Syst. Softw., Vol.81, No.5, pp.649-660, May 2008.
E. Arisholm, L. C. Briand, and E. B. Johannessen, "A systematic and comprehensive investigation of methods to build and evaluate fault prediction models," J. Syst. Softw., Vol.83, No.1, pp.2-17, Jan. 2010.
T. Hall, S. Beecham, D. Bowes, D. Gray, and S. Counsell, "A Systematic Literature Review on Fault Prediction Performance in Software Engineering," IEEE Trans. Softw. Eng., Vol.38, No.6, pp.1276-1304, Nov. 2012.
T. Menzies, Z. Milton, B. Turhan, B. Cukic, Y. Jiang, and A. Bener, "Defect prediction from static code features: current results, limitations, new approaches," Autom. Softw. Eng., Vol.17, No.4, pp.375-407, May 2010.
M. D'Ambros, M. Lanza, and R. Robbes, "Evaluating defect prediction approaches: A benchmark and an extensive comparison," Empir. Softw. Eng., Vol.17, No.4-5, pp.531-577, Aug. 2012.
T. Zimmermann, N. Nagappan, H. Gall, E. Giger, and B. Murphy, "Cross-project defect prediction," in Proceedings of the 7th Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on The Foundations of Software Engineering, pp.91-100, 2009.
Z. He, F. Shu, Y. Yang, M. Li, and Q. Wang, "An investigation on the feasibility of cross-project defect prediction," Autom. Softw. Eng., Vol.19, No.2, pp.167-199, Jul. 2011.
Y. Ma, G. Luo, X. Zeng, and A. Chen, "Transfer learning for cross-company software defect prediction," Inf. Softw. Technol., Vol.54, No.3, pp.248-256, Mar. 2012.
J. Nam, S. J. Pan, and S. Kim, "Transfer defect learning," in Proceedings of the 35th International Conference on Software Engineering, pp.382-391, 2013.
D. Ryu, J. Jang, and J. Baik, "A Hybrid Instance Selection using Nearest-Neighbor for Cross-Project Defect Prediction," J. Comput. Sci. Technol., Vol.30, No.5, pp.969-980, 2015.
G. Woodbury, "An Introduction to Statistics." Cengage Learning, 2001.
D. Ryu, O. Choi, and J. Baik, "Value-cognitive boosting with a support vector machine for cross-project defect prediction," Empir. Softw. Eng., Vol.21, No.1, pp.43-71, Feb. 2016.
B. Turhan, T. Menzies, A. B. Bener, and J. Di Stefano, "On the relative value of cross-company and within-company data for defect prediction," Empir. Softw. Eng., Vol.14, No.5, pp.540-578, Jan. 2009.
T. Pang-Ning, M. Steinbach, and V. Kumar, "Introduction to Data Mining." 2006.
T. Grbac, G. Mausa, and B. Basic, "Stability of Software Defect Prediction in Relation to Levels of Data Imbalance.," in Proceedings of the 2nd Workshop of SQAMIA, 2013.
N. V Chawla, K. W. Bowyer, L. O. Hall, and W. P. Kegelmeyer, "SMOTE : Synthetic Minority Over-sampling Technique," J. Artif. Intell. Res., Vol.16, pp.321-357, 2002.
C. C. Aggarwal, "Outlier Analysis." New York, NY: Springer New York, 2013.
H.-P. Kriegel, M. Schubert, and A. Zimek, "Angle-based outlier detection in high-dimensional data," Proceeding 14th ACM SIGKDD Int. Conf. Knowl. Discov. Data Min. (KDD '08), pp.444-452, 2008.
N. Altman, "An introduction to kernel and nearest-neighbor nonparametric regression," Am. Stat., Vol.46, No.3, pp.175-185, 1992.
R. Hamming, "Error Detecting and Error Correcting Codes," Bell Syst. Tech. J., Vol.XXIX, No.2, 1950.
B. Raman and T. R. Ioerger, "Enhancing Learning using Feature and Example selection," Texas A&M Univ. Coll. Station. TX, USA, 2003.
E. Parzen, "On estimation of a probability density function and mode," Ann. Math. Stat., Vol.33, No.3, pp.1065-1076, 1962.
M. Breunig, H. Kriegel, R. Ng, and J. Sander, "LOF: identifying density-based local outliers," ACM Sigmod Rec., pp.1-12, 2000.
S. Papadimitriou, H. Kitagawa, P. B. Gibbons, and C. Faloutsos, "LOCI: Fast outlier detection using the local correlation integral," Proc. - Int. Conf. Data Eng., pp.315-326, 2003.
S. Lloyd, "Least squares quantization in PCM," IEEE Trans. Inf. Theory, Vol.28, No.2, pp.129-137, 1982.
I. T. Jolliffe, "Principal Component Analysis." Springer, 2002.
T. Kohonen, "Self-organized formation of topologically correct feature maps," Biol. Cybern., Vol.43, No.1, pp.59-69, 1982.
C. M. Bishop, "Pattern recognition and machine learning." New York, New York, USA: Springer, 2006.
B. Turhan, A. Tosun MIsirli, and A. Bener, "Empirical evaluation of the effects of mixed project data on learning defect predictors," Inf. Softw. Technol., Vol.55, No.6, pp.1101-1118, Jun. 2013.
M. Jureczko and D. Spinellis, "Using Object-Oriented Design Metrics to Predict Software Defects," in Models and Methods of System Dependability. Oficyna Wydawnicza Politechniki Wroclawskiej, 2010, pp.69-81.
T. Menzies et al., "The PROMISE Repository of empirical software engineering data," 2012. [Online]. Available: http://openscience.us/repo/.
K. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft, When is "nearest neighbor" meaningful? Springer-Verlag, 1999.
S. Lessmann, B. Baesens, C. Mues, and S. Pietsch, "Benchmarking Classification Models for Software Defect Prediction: A Proposed Framework and Novel Findings," IEEE Trans. Softw. Eng., Vol.34, No.4, pp.485-496, 2008.
M. Hall, E. Frank, and G. Holmes, "The WEKA data mining software: an update," ACM SIGKDD Explor. Newsl., Vol.11, No.1, pp.10-18, 2009.
P. C. Mahalanobis, "On the generalised distance in statistics," in Proceedings of the National Institute of Sciences of India, Vol.2, No.1, pp.49-55, 1936.
F. Menzies T, Greenwald J, "Data mining static code attributes to learn defect predictors," IEEE Trans. Softw. Eng., Vol.33, No.1, pp.2-13, 2007.
B. Turhan, A. Tosun, and A. Bener, "Empirical Evaluation of Mixed-Project Defect Prediction Models," in Proceedings of the 37th EUROMICRO Conference on Software Engineering and Advanced Applications, pp.396-403, 2011.
Y. Kamei, S. Matsumoto, A. Monden, K. I. Matsumoto, B. Adams, and A. E. Hassan, "Revisiting common bug prediction findings using effort-aware models," IEEE Int. Conf. Softw. Maintenance, ICSM, 2010.
S. Wang and X. Yao, "Using Class Imbalance Learning for Software Defect Prediction," IEEE Trans. Reliab., Vol.62, No.2, pp.434-443, Jun. 2013.
M. Friedman, "The use of ranks to avoid the assumption of normality implicit in the analysis of variance," J. Am. Stat. Assoc., No.32, pp.675-701, 1937.
M. Friedman, "A comparison of alternative tests of significance for the problem of m rankings.," Ann. Math. Stat., No.11, pp.86-92, 1940.
J. Demsar, "Statistical comparisons of classifiers over multiple data sets," J. Mach. Learn. Res., Vol.7, pp.1-30, 2006.
J. Tukey, "Comparing individual means in the analysis of variance," Biometrics, No.5, pp.99-114, 1949.
P. Nemenyi, "Distribution-free multiple comparisons.," Princeton University, 1963.
O. J. Dunn, "Multiple comparisons among means," J. Am. Stat. Assoc., No.56, pp.52-64, 1961.
F. Wilcoxon, "Individual comparisons by ranking methods," Biometrics Bull., pp.80-83, 1945.
A. Arcuri and L. Briand, "A practical guide for using statistical tests to assess randomized algorithms in software engineering," in 2011 33rd International Conference on Software Engineering (ICSE), pp.1-10, 2011.
A. Vargha and H. D. Delaney, "A Critique and Improvement of the CL Common Language Effect Size Statistics of McGraw and Wong," J. Educ. Behav. Stat., Vol.25, No.2, pp.101-132, 2000.
D. M. J. Tax, "DDtools, the Data Description Toolbox for Matlab." 2014.
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